By employing T-S fuzzy system to approximate uncertain functions, an adaptive fuzzy control algorithm was developed based on dynamic surface control and minimal-learning-parameter algorithm. With less learning parameters and reduced computation load, the proposed algorithm is convenient to be implemented in applications, and can avoid the possible controller singularity problem. In addition, the boundedness stability of the closed-loop system is guaranteed and the tracking error can be made arbitrarily small. Simulation results validate the effectiveness and the performance of the proposed scheme.
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